The present invention relates to optical lenses having an inherent non-uniform parameter and their image on a given camera system. More specifically, the invention relates to a method for designing an optimization apparatus to be used with these cameras and lenses with non-uniform parameters to improve the overall performance of the system. This optimization apparatus can be used for calibration, tuning, measuring, testing or the like.
For regular optical lenses having no significant non-uniform parameters, there are many existing kinds of optimization apparatuses for optimizing the performance of the cameras. Such apparatuses include an optical bench or an enclosure box in which one or more objects having precise shapes or characteristics are placed at precise locations in order to create some constant conditions for the optimization of performance. This optimization includes calibration, tuning, characterization, and more. Objects commonly found on these benches or inside these boxes includes common charts, light sources with well-known emission spectra and intensities, everyday familiar objects or shapes (including human-shaped dummies), light diffusers, items with specific color or shades of grey, or the like. More specifically, common existing charts include some brightness charts (with pre-defined patches of black, grey and white), color charts (with pre-defined patches of color), resolution charts (with combinations of vertical and horizontal alternating black and white lines of different spacing), distortion charts (with a known position in object space of various grid points), image quality charts (with slanted edge parallelograms for numerical image quality or Siemens stars for visual image quality), and more.
With the existing optimization apparatus, the analysis of the results and the corresponding tuning of the camera are most often automated by software programs. The rest of the time, these analyses are done manually using more subjective criteria depending on the person viewing the resulting images. A program or a human viewing the images can recognize the exact objects inside the images as well as the conditions used to capture the images, including the light spectrum and the light intensity. For common objects that are usually part of these existing optimization apparatuses, the programs can also do mathematical calculations based on the image of the objects through the camera system while the human can do subjective comparisons based on experience with other lens and camera systems.
However, when the optical lens in the camera system has a non-uniform parameter, such as distortion, magnification, relative illumination, resolution, image quality (MTF), anamorphic ratio between two principal axes and the like, the captured images of these existing optimization apparatuses are deformed or altered. The consequence of these deformed or altered images is that the existing automated analysis (e.g., tuning) software cannot recognize the objects, or an incorrect analysis is provided due to the different information being processed. For human analysis of the images, the unusual shape, color, or texture of the objects visible inside the images also make it harder to compare the results with images from standard lenses having no significant non-uniform parameters.
Furthermore, one common example of lenses with a non-uniform parameter is a lens with optical distortion having non-uniform magnification across the field of view. These lenses often have wide-angle field of view. When using these lenses on an existing optimization apparatus, such as a conventional bench or inside a conventional box, the useful objects for the analysis and tuning are often placed in only a central part of the field of view and nothing useful is imaged at the edges of the field of view. Worse, light sources used to create uniform lighting conditions in the image and that shouldn't be part of the image may be imaged by these wide-angle lenses. With these wide-angle lenses, the objects also cover significantly less pixels, making the interpretation of the images by a software program or a human even more challenging.
For all these reasons, most of the existing optimization apparatuses for standard lenses cannot be readily used with cameras having lenses with a non-uniform parameter. For some of the issues, as the deformed image of the objects, one solution is to modify the software programs. However, this solution is often not possible or desirable for the final user because it requires access to the source code, as well as the skill and the time to modify the program accordingly. Another solution could be to correct the non-uniformity in the image at the software level before using it in the existing optimization software programs. This idea is, however, often impossible because pre-processing the image has the undesirable effect of modifying or destroying some important characteristics of the original image, including the noise information or information found in the Bayer pattern from the sensor. In these cases, the optimization programs must be used on the raw images from the camera without any pre-processing.
For images from a wide-angle lens, in addition of the existing software being incompatible with the distorted images, the lack of charts or objects and the undesirable presence of other objects not normally imaged at the edge of the field of view are also problematic and make the automated tuning impossible. Also, the lower number of pixels on the objects of interest when viewed with wide-angle lenses affects the calculations, and even rewriting the program to adapt for the deformed shapes is not a workable solution because the metrics are not comparable with low numbers of pixels, as compared to standard lenses and the high number of pixels in their images for given objects.
Custom optimization apparatuses for systems having an optical lens with non-uniform parameters have been used in the past. When the non-uniform parameter is distortion, these include custom charts designed specifically to be independent of the image distortion, as proposed in U.S. Pat. No. 7,852,513, by using radially distributed color charts. However, these charts require the use of a special software program and cannot be used with the existing software already programmed to use the existing standard charts. Also, because the center must be on the optical axis of the lens, radial charts can only be used in the center of the field of view of the distorting lens. Placed in any other part of the field of view, the shapes of these charts will be deformed in the images and unusable, greatly limiting their use to one chart at a time and at a fixed position in the center. An ideal optimization apparatus for lenses having optical distortion, including wide-angle lenses, should have many charts and objects located at various locations inside the field of view, and radial charts limited to the center cannot be used. Furthermore, the idea of a radial color chart cannot be used for other kinds of 2D or 3D objects, like resolution charts or human dummies.
Another issue is the lighting condition in existing optimization apparatuses. Many existing lens and camera optimization boxes have a highly controlled light intensity, uniformity, and spectrum in an area of the box where charts and objects are located, but have non-uniform light or even shadows present in other parts of the box not typically imaged by standard lenses. With wide-angle lenses having a field of view over 180°, the lens can see even behind the camera, and the existing boxes cannot be used to create uniform lighting conditions for the image.
Many existing systems and apparatuses have been proposed in the past to calibrate lenses with optical distortion, including in U.S. Pat. No. 8,619,248. However, these apparatuses are made of targets at exactly known locations and are used to measure the exact distortion profile of some lenses with optical distortion and cannot be used to produce images outputted from the camera that appear without optical distortion. These existing calibration method cannot be used with existing software programs used to calibrate, test, and tune standard optical lenses without optical distortion.